for blog post 2

decisionTreeClassifier.py

from sklearn.tree import DecisionTreeClassifier
myClassifier2 = DecisionTreeClassifier(max_depth = 5, min_samples_leaf = 2)
myClassifier2.fit(X_train, y_train)
predictions2 = myClassifier2.predict(X_test)

cnf2 = confusion_matrix(y_test, predictions2)
score2 = accuracy_score(y_test, predictions2)

print ("Confusion Matrix for our Decision Tree classifier is :\n ", cnf2)

print("While the accuracy score for the same is %.2f percent" % (score2 * 100))